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Wendy Martin

Engineering and Business professionals often have access to many sources of data. The best way to way to ensure your data is both valid and reliable is to plan for it ahead of time. Through this class, you will be able to plan for accurate and precise data generation, then use that data for the purpose of estimation and risk reduction related to capital investments.

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Engineering and Business professionals often have access to many sources of data. The best way to way to ensure your data is both valid and reliable is to plan for it ahead of time. Through this class, you will be able to plan for accurate and precise data generation, then use that data for the purpose of estimation and risk reduction related to capital investments.

This specialization can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.

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What's inside

Syllabus

Fundamentals of Sampling
Upon completion of this module, students will be able to classify types of sampling used for data acquisition, describe sampling error, and construct random number sequences for sampling.
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Estimation
Upon completion of this module, students will be able to calculate point and interval estimates using RStudio and ROIStat.
Best Case / Worst Case Analysis
Upon completion of this module, students will be able to use point and interval estimates to determine best- and worst-case scenarios.
Foundations of Hypothesis Testing
Upon completion of this module, students will be able to plan for data acquisition to minimize risk in decision making, including sample size, effect size and power calculations.
Essentials for Effect Size Calculations
Upon completion of this module, students will be able to use return on investment calculations to determine effect size, sample size and power using RStudio and ROIStat.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Taught by Wendy Martin, a leader and innovator in the field of data collection and analysis
Highly relevant toward risk assessment for capital investment
Covers best case and worst case scenario analysis
Involves hands-on practice using RStudio and ROIstat software
Requires a strong foundation in statistics and probability
Students are expected to have access to specialized software and hardware

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Acquisition, Risk, and Estimation with these activities:
Follow a tutorial on using RStudio for data analysis
Follow a tutorial on using RStudio to gain hands-on experience with data analysis.
Browse courses on RStudio
Show steps
  • Find a tutorial on using RStudio for data analysis.
  • Follow the steps in the tutorial to learn how to use RStudio.
Review the book 'Statistics for Business and Economics' by Anderson, Sweeney, Williams, and Camm
Review the textbook to strengthen foundational knowledge in statistics.
Show steps
  • Read the assigned chapters in the textbook.
  • Complete the practice problems at the end of each chapter.
Write a blog post on the importance of data validity and reliability
Write a blog post to reinforce the importance of data validity and reliability in decision-making.
Show steps
  • Research the topic of data validity and reliability.
  • Write a blog post that explains the importance of data validity and reliability.
Four other activities
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Show all seven activities
Estimate the accuracy of measurements based on digit use
Practice estimating the accuracy of measurements to improve understanding of the concept of sampling error.
Browse courses on Sampling
Show steps
  • Read through the course materials on sampling error.
  • Solve practice problems on estimating accuracy.
Attend a workshop on data visualization techniques
Attend a workshop on data visualization techniques to learn how to present data in a clear and concise manner.
Browse courses on Data Visualization
Show steps
  • Find a workshop on data visualization techniques.
  • Attend the workshop and learn about different data visualization techniques.
Design a sampling plan for a specific scenario
Create a real-world sampling plan to reinforce the principles of sampling design.
Browse courses on Sampling
Show steps
  • Identify the population of interest and the information needed.
  • Determine the sampling method and sample size.
  • Collect the data and analyze the results.
Build a data dashboard to track key performance indicators
Build a data dashboard to practice data analysis and presentation skills.
Show steps
  • Identify the key performance indicators that you want to track.
  • Collect the data that you need to track the key performance indicators.
  • Build a data dashboard to visualize the data.
  • Use the data dashboard to track the key performance indicators and make informed decisions.

Career center

Learners who complete Data Acquisition, Risk, and Estimation will develop knowledge and skills that may be useful to these careers:
Risk Manager
Risk Managers identify, assess, and mitigate risks that may impact an organization's operations or finances. The Data Acquisition, Risk, and Estimation course would be highly relevant to Risk Managers, providing them with a comprehensive understanding of risk assessment techniques, data analysis methods, and strategies for risk management.
Data Analyst
Data Analysts use various techniques to collect, clean, analyze, and present data, which is essential for driving informed decision-making. The Data Acquisition, Risk, and Estimation course at the University of Colorado Boulder would be highly relevant to aspiring Data Analysts, providing them with a solid foundation in data sampling, estimation, hypothesis testing, and risk assessment. These skills are crucial for extracting meaningful insights from data and making accurate predictions.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make investment decisions. The Data Acquisition, Risk, and Estimation course would be highly beneficial to aspiring Quantitative Analysts, providing them with a solid foundation in data analysis, risk assessment, and statistical modeling. These skills are essential for developing and implementing profitable investment strategies.
Actuary
Actuaries use mathematical and statistical techniques to assess and manage financial risk. The Data Acquisition, Risk, and Estimation course at the University of Colorado Boulder would be valuable to aspiring Actuaries, providing them with a strong foundation in probability, statistics, and risk modeling. These skills are crucial for developing and implementing effective risk management strategies.
Statistician
Statisticians use data to make inferences about populations. The Data Acquisition, Risk, and Estimation course at the University of Colorado Boulder would be highly relevant to aspiring Statisticians, providing them with a strong foundation in probability, statistics, and data analysis. These skills are crucial for designing and conducting effective statistical studies.
Survey Researcher
Survey Researchers design and conduct surveys to collect data about populations. The Data Acquisition, Risk, and Estimation course would be highly beneficial to aspiring Survey Researchers, providing them with skills in survey design, data analysis, and sampling techniques. These skills are essential for conducting valid and reliable surveys.
Business Analyst
Business Analysts use data to identify and solve business problems. The Data Acquisition, Risk, and Estimation course at the University of Colorado Boulder would be highly relevant to aspiring Business Analysts, providing them with skills in data acquisition, analysis, and modeling. These skills are essential for developing and implementing effective business solutions.
Market Research Analyst
Market Research Analysts conduct surveys, interviews, and other research methods to gather data about target markets and consumer behavior. The Data Acquisition, Risk, and Estimation course would be beneficial to Market Research Analysts, helping them design effective data collection strategies, analyze data accurately, and mitigate risks associated with data interpretation.
Epidemiologist
Epidemiologists study the distribution and determinants of health-related states or events in populations. The Data Acquisition, Risk, and Estimation course at the University of Colorado Boulder would be valuable to aspiring Epidemiologists, providing them with skills in data acquisition, analysis, and risk assessment. These skills are essential for identifying and preventing health risks in populations.
Data Scientist
Data Scientists use data to build models and solve complex problems. The Data Acquisition, Risk, and Estimation course would be valuable to aspiring Data Scientists, providing them with skills in data acquisition, analysis, and modeling. These skills are essential for developing and implementing effective data science solutions.
Quality Assurance Manager
Quality Assurance Managers oversee the quality of products or services. The Data Acquisition, Risk, and Estimation course at the University of Colorado Boulder would be valuable to aspiring Quality Assurance Managers, providing them with skills in data analysis, risk assessment, and quality control. These skills are essential for ensuring that products or services meet quality standards.
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to improve the efficiency of operations. The Data Acquisition, Risk, and Estimation course at the University of Colorado Boulder would be valuable to aspiring Operations Research Analysts, providing them with skills in data analysis, modeling, and risk assessment. These skills are essential for developing and implementing effective operations research solutions.
Financial Analyst
Financial Analysts use data to evaluate the financial performance and prospects of companies, industries, and investments. The course at the University of Colorado Boulder would be valuable to aspiring Financial Analysts, providing them with skills in data acquisition, estimation, and risk analysis. These skills are essential for making sound investment decisions.
Technical Writer
Technical Writers create documentation for technical products or services. The Data Acquisition, Risk, and Estimation course would be beneficial to aspiring Technical Writers, providing them with skills in data analysis, risk assessment, and technical writing. These skills are essential for developing clear and accurate technical documentation.
Project Manager
Project Managers plan, execute, and close projects. The Data Acquisition, Risk, and Estimation course would be helpful to aspiring Project Managers, providing them with skills in project planning, risk management, and data analysis. These skills are essential for managing projects successfully.

Reading list

We've selected ten books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Acquisition, Risk, and Estimation.
This textbook provides a comprehensive overview of statistical methods for engineers and scientists. It covers topics such as data collection, analysis, and presentation, and it includes numerous examples and exercises to help students learn the material.
Provides a practical guide to statistical methods for quality improvement. It covers topics such as data collection, analysis, and interpretation, and it includes numerous case studies to help students apply the material to real-world problems.
Provides a comprehensive overview of Bayesian data analysis. It covers topics such as Bayesian inference, model selection, and computational methods, and it includes numerous examples and exercises to help students learn the material.
Provides a comprehensive overview of data-driven science and engineering. It covers topics such as data mining, machine learning, and statistical modeling, and it includes numerous examples and exercises to help students learn the material.
Provides a practical guide to data analysis with Pandas. It covers topics such as data manipulation, data visualization, and statistical analysis, and it includes numerous examples and exercises to help students learn the material.
Provides a practical guide to data science for business. It covers topics such as data mining, machine learning, and statistical modeling, and it includes numerous examples and exercises to help students learn the material.
Provides a comprehensive overview of big data analytics. It covers topics such as data mining, machine learning, and statistical modeling, and it includes numerous examples and exercises to help students learn the material.
Provides a comprehensive overview of data science. It covers topics such as data mining, machine learning, and statistical modeling, and it includes numerous examples and exercises to help students learn the material.

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